de.lmu.ifi.dbs.elki.math.linearalgebra.pca
Class PCAFilteredResult

java.lang.Object
  de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult
      de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult

All Implemented Interfaces:

ProjectionResult

public class PCAFilteredResult
extends PCAResult
implements ProjectionResult

Result class for a filtered PCA. This differs from regular PCA by having the Eigenvalues and Eigenvectors separated into "strong" and "weak" Eigenvectors, and thus a dimension. Usually this will be interpreted as having a "data" subspace and an "error" subspace.

Field Summary

private Matrix	adapatedStrongEigenvectors The diagonal matrix of adapted strong eigenvalues: eigenvectors * e_czech.
private Matrix	e_czech The selection matrix of the strong eigenvectors.
private Matrix	e_hat The selection matrix of the weak eigenvectors.
private double	explainedVariance The amount of Variance explained by strong Eigenvalues
private Matrix	m_czech The dissimilarity matrix.
private Matrix	m_hat The similarity matrix.
private double[]	strongEigenvalues The strong eigenvalues.
private Matrix	strongEigenvectors The strong eigenvectors to their corresponding filtered eigenvalues.
private double[]	weakEigenvalues The weak eigenvalues.
private Matrix	weakEigenvectors The weak eigenvectors to their corresponding filtered eigenvalues.

Constructor Summary

PCAFilteredResult(SortedEigenPairs eigenPairs, FilteredEigenPairs filteredEigenPairs, double big, double small)
Construct a result object for the filtered PCA result.

Method Summary

Matrix	adapatedStrongEigenvectors() Returns a copy of the adapted strong eigenvectors.
Matrix	dissimilarityMatrix() Returns a copy of the dissimilarity matrix (M_czech) of this LocalPCA.
int	getCorrelationDimension() Get correlation (subspace) dimensionality
double	getExplainedVariance() Returns explained variance
double[]	getStrongEigenvalues() Returns a copy of the strong eigenvalues of the object after passing the eigen pair filter.
Matrix	getStrongEigenvectors() Returns a copy of the matrix of strong eigenvectors after passing the eigen pair filter.
double[]	getWeakEigenvalues() Returns a copy of the weak eigenvalues of the object after passing the eigen pair filter.
Matrix	getWeakEigenvectors() Returns a copy of the matrix of weak eigenvectors after passing the eigen pair filter.
Matrix	selectionMatrixOfStrongEigenvectors() Returns a copy of the selection matrix of the strong eigenvectors (E_czech) of this LocalPCA.
Matrix	selectionMatrixOfWeakEigenvectors() Returns a copy of the selection matrix of the weak eigenvectors (E_hat) of the object to which this PCA belongs to.
Matrix	similarityMatrix() Returns a copy of the similarity matrix (M_hat) of this LocalPCA.

Methods inherited from class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult

getEigenPairs, getEigenvalues, getEigenvectors, length

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

strongEigenvalues

private double[] strongEigenvalues

The strong eigenvalues.

strongEigenvectors

private Matrix strongEigenvectors

The strong eigenvectors to their corresponding filtered eigenvalues.

weakEigenvalues

private double[] weakEigenvalues

The weak eigenvalues.

weakEigenvectors

private Matrix weakEigenvectors

The weak eigenvectors to their corresponding filtered eigenvalues.

explainedVariance

private double explainedVariance

The amount of Variance explained by strong Eigenvalues

e_hat

private Matrix e_hat

The selection matrix of the weak eigenvectors.

e_czech

private Matrix e_czech

The selection matrix of the strong eigenvectors.

m_hat

private Matrix m_hat

The similarity matrix.

m_czech

private Matrix m_czech

The dissimilarity matrix.

adapatedStrongEigenvectors

private Matrix adapatedStrongEigenvectors

The diagonal matrix of adapted strong eigenvalues: eigenvectors * e_czech.

Constructor Detail

PCAFilteredResult

public PCAFilteredResult(SortedEigenPairs eigenPairs,
                         FilteredEigenPairs filteredEigenPairs,
                         double big,
                         double small)

Construct a result object for the filtered PCA result.

Parameters:

eigenPairs - All EigenPairs

filteredEigenPairs - filtered EigenPairs

big - large value in selection matrix

small - small value in selection matrix

Method Detail

getStrongEigenvectors

public final Matrix getStrongEigenvectors()

Returns a copy of the matrix of strong eigenvectors after passing the eigen pair filter.

Returns:

the matrix of eigenvectors

getStrongEigenvalues

public final double[] getStrongEigenvalues()

Returns a copy of the strong eigenvalues of the object after passing the eigen pair filter.

Returns:

the eigenvalues

getWeakEigenvectors

public final Matrix getWeakEigenvectors()

Returns a copy of the matrix of weak eigenvectors after passing the eigen pair filter.

Returns:

the matrix of eigenvectors

getWeakEigenvalues

public final double[] getWeakEigenvalues()

Returns a copy of the weak eigenvalues of the object after passing the eigen pair filter.

Returns:

the eigenvalues

getCorrelationDimension

public final int getCorrelationDimension()

Get correlation (subspace) dimensionality

Specified by:

getCorrelationDimension in interface ProjectionResult

Returns:

length of strong eigenvalues

getExplainedVariance

public double getExplainedVariance()

Returns explained variance

Returns:

the variance explained by the strong Eigenvectors

selectionMatrixOfWeakEigenvectors

public Matrix selectionMatrixOfWeakEigenvectors()

Returns a copy of the selection matrix of the weak eigenvectors (E_hat) of the object to which this PCA belongs to.

Returns:

the selection matrix of the weak eigenvectors E_hat

selectionMatrixOfStrongEigenvectors

public Matrix selectionMatrixOfStrongEigenvectors()

Returns a copy of the selection matrix of the strong eigenvectors (E_czech) of this LocalPCA.

Returns:

the selection matrix of the weak eigenvectors E_czech

similarityMatrix

public Matrix similarityMatrix()

Returns a copy of the similarity matrix (M_hat) of this LocalPCA.

Specified by:

similarityMatrix in interface ProjectionResult

Returns:

the similarity matrix M_hat

dissimilarityMatrix

public Matrix dissimilarityMatrix()

Returns a copy of the dissimilarity matrix (M_czech) of this LocalPCA.

Returns:

the dissimilarity matrix M_hat

adapatedStrongEigenvectors

public Matrix adapatedStrongEigenvectors()

Returns a copy of the adapted strong eigenvectors.

Returns:

the adapted strong eigenvectors